{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入包\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "pd.set_option('display.max_columns',None) # 设置DataFrame最大展示列数P\n",
    "pd.set_option('display.max_rows',10) # 设置DataFrame最大展示行数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(r\"D:\\2、自我文件\\knowledge-base\\pandas\\data\\population.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LOCATION</th>\n",
       "      <th>INDICATOR</th>\n",
       "      <th>SUBJECT</th>\n",
       "      <th>MEASURE</th>\n",
       "      <th>FREQUENCY</th>\n",
       "      <th>TIME</th>\n",
       "      <th>Value</th>\n",
       "      <th>Flag Codes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AUS</td>\n",
       "      <td>POP</td>\n",
       "      <td>TOT</td>\n",
       "      <td>AGRWTH</td>\n",
       "      <td>A</td>\n",
       "      <td>1957</td>\n",
       "      <td>2.270316</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AUS</td>\n",
       "      <td>POP</td>\n",
       "      <td>TOT</td>\n",
       "      <td>AGRWTH</td>\n",
       "      <td>A</td>\n",
       "      <td>1958</td>\n",
       "      <td>2.095436</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AUS</td>\n",
       "      <td>POP</td>\n",
       "      <td>TOT</td>\n",
       "      <td>AGRWTH</td>\n",
       "      <td>A</td>\n",
       "      <td>1959</td>\n",
       "      <td>2.174355</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AUS</td>\n",
       "      <td>POP</td>\n",
       "      <td>TOT</td>\n",
       "      <td>AGRWTH</td>\n",
       "      <td>A</td>\n",
       "      <td>1960</td>\n",
       "      <td>2.177804</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AUS</td>\n",
       "      <td>POP</td>\n",
       "      <td>TOT</td>\n",
       "      <td>AGRWTH</td>\n",
       "      <td>A</td>\n",
       "      <td>1961</td>\n",
       "      <td>2.269586</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9558</th>\n",
       "      <td>LVA</td>\n",
       "      <td>POP</td>\n",
       "      <td>WOMEN</td>\n",
       "      <td>MLN_PER</td>\n",
       "      <td>A</td>\n",
       "      <td>2008</td>\n",
       "      <td>1.177000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9559</th>\n",
       "      <td>LVA</td>\n",
       "      <td>POP</td>\n",
       "      <td>WOMEN</td>\n",
       "      <td>MLN_PER</td>\n",
       "      <td>A</td>\n",
       "      <td>2009</td>\n",
       "      <td>1.160000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9560</th>\n",
       "      <td>LVA</td>\n",
       "      <td>POP</td>\n",
       "      <td>WOMEN</td>\n",
       "      <td>MLN_PER</td>\n",
       "      <td>A</td>\n",
       "      <td>2010</td>\n",
       "      <td>1.138000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9561</th>\n",
       "      <td>LVA</td>\n",
       "      <td>POP</td>\n",
       "      <td>WOMEN</td>\n",
       "      <td>MLN_PER</td>\n",
       "      <td>A</td>\n",
       "      <td>2011</td>\n",
       "      <td>1.118000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9562</th>\n",
       "      <td>LVA</td>\n",
       "      <td>POP</td>\n",
       "      <td>WOMEN</td>\n",
       "      <td>MLN_PER</td>\n",
       "      <td>A</td>\n",
       "      <td>2012</td>\n",
       "      <td>1.104000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9563 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     LOCATION INDICATOR SUBJECT  MEASURE FREQUENCY  TIME     Value Flag Codes\n",
       "0         AUS       POP     TOT   AGRWTH         A  1957  2.270316        NaN\n",
       "1         AUS       POP     TOT   AGRWTH         A  1958  2.095436        NaN\n",
       "2         AUS       POP     TOT   AGRWTH         A  1959  2.174355        NaN\n",
       "3         AUS       POP     TOT   AGRWTH         A  1960  2.177804        NaN\n",
       "4         AUS       POP     TOT   AGRWTH         A  1961  2.269586        NaN\n",
       "...       ...       ...     ...      ...       ...   ...       ...        ...\n",
       "9558      LVA       POP   WOMEN  MLN_PER         A  2008  1.177000        NaN\n",
       "9559      LVA       POP   WOMEN  MLN_PER         A  2009  1.160000        NaN\n",
       "9560      LVA       POP   WOMEN  MLN_PER         A  2010  1.138000        NaN\n",
       "9561      LVA       POP   WOMEN  MLN_PER         A  2011  1.118000        NaN\n",
       "9562      LVA       POP   WOMEN  MLN_PER         A  2012  1.104000        NaN\n",
       "\n",
       "[9563 rows x 8 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "7945e9a82d7512fbf96246d9bbc29cd2f106c1a4a9cf54c9563dadf10f2237d4"
  },
  "kernelspec": {
   "display_name": "Python 3.7.9 64-bit",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.9"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
